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跨感觉学习:多感觉统计学习中的跨模态效应。

Learning across senses: cross-modal effects in multisensory statistical learning.

机构信息

Department of Psychology and Program in Linguistics, Pennsylvania State University, 643 Moore Building, University Park, PA 16802, USA.

出版信息

J Exp Psychol Learn Mem Cogn. 2011 Sep;37(5):1081-91. doi: 10.1037/a0023700.

Abstract

It is currently unknown whether statistical learning is supported by modality-general or modality-specific mechanisms. One issue within this debate concerns the independence of learning in one modality from learning in other modalities. In the present study, the authors examined the extent to which statistical learning across modalities is independent by simultaneously presenting learners with auditory and visual streams. After establishing baseline rates of learning for each stream independently, they systematically varied the amount of audiovisual correspondence across 3 experiments. They found that learners were able to segment both streams successfully only when the boundaries of the audio and visual triplets were in alignment. This pattern of results suggests that learners are able to extract multiple statistical regularities across modalities provided that there is some degree of cross-modal coherence. They discuss the implications of their results in light of recent claims that multisensory statistical learning is guided by modality-independent mechanisms.

摘要

目前尚不清楚统计学习是由模态通用机制还是模态特定机制支持的。这场争论中的一个问题涉及到一种模态中的学习与其他模态中的学习的独立性。在本研究中,作者通过同时向学习者呈现听觉和视觉流来检查跨模态统计学习的独立性程度。在为每个流独立建立学习的基线率之后,他们在 3 个实验中系统地改变了视听对应关系的数量。他们发现,只有当音频和视觉三连体的边界对齐时,学习者才能成功地分割两个流。这一结果模式表明,只要存在某种程度的跨模态连贯性,学习者就能够从跨模态中提取多个统计规律。他们根据最近关于多感觉统计学习由独立于模态的机制指导的说法,讨论了他们的结果的意义。

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